The First Nations, Métis, Inuit Indigenous Ontology and Challenges in the Development of an Indigenous Community Vocabulary in the Canadian Context
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Creating and implementing Indigenous-led thesauri and vocabularies for wide adoption by cultural memory institutions is essential to providing respectful terminology to describe materials by and about Indigenous peoples in the territory referred to as Canada. This article details the background, creation, and reflections on the First Nation, Métis, and Inuit, Indigenous Ontology (FNMIIO), up to the release of the first draft in June 2019 as well as more recent initiatives and transformations. Grounded in the recommendations developed by the Canadian Federation of Library Associations’ (CFLA) Truth and Reconciliation Committee, the article discusses the creation of the FNMIIO as an important first step in addressing the need for a widely adoptable, Indigenous run and led thesaurus for use in cultural memory institutions. The article discusses both the methods undertaken in the project and the challenges faced in the development of the FNMIIO and connects the challenges to issues in libraries and the cultural heritage sector in the territory known as Canada as a whole. While a crucial proof-of-concept, the FNMIIO exposed several important issues that must be addressed to fully develop the thesaurus, particularly with respect to ensuring the longevity of the project. While much work remains to make the FNMIIO fully usable by institutions, the initial lessons learned by the CFLA Indigenous Matters Committee’s Joint Working Group as they progressed through the gathering of community names will undergird the next steps for the development and deployment of the FNMIIO.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it